getGenomeAndAnnotation: Download genome (fasta), annotation (GTF) and contaminants
In Roleren/ORFik: Open Reading Frames in Genomics

getGenomeAndAnnotation

R Documentation

Download genome (fasta), annotation (GTF) and contaminants

Description

This function automatically downloads (if files not already exists) genomes and contaminants specified for genome alignment. By default, it will use ensembl reference, upon completion, the function will store a file called file.path(output.dir, "outputs.rds") with the output paths of your completed genome/annotation downloads. For most non-model nonvertebrate organisms, you need my fork of biomartr for it to work: remotes::install_github("Roleren/biomartr) If you misspelled something or crashed, delete wrong files and run again.
Do remake = TRUE, to do it all over again.

Usage

getGenomeAndAnnotation(
  organism,
  output.dir,
  db = "ensembl",
  GTF = TRUE,
  genome = TRUE,
  merge_contaminants = TRUE,
  phix = FALSE,
  ncRNA = FALSE,
  tRNA = FALSE,
  rRNA = FALSE,
  gunzip = TRUE,
  remake = FALSE,
  assembly_type = c("primary_assembly", "toplevel"),
  optimize = FALSE,
  gene_symbols = FALSE,
  uniprot_id = FALSE,
  pseudo_5UTRS_if_needed = NULL,
  remove_annotation_outliers = TRUE,
  notify_load_existing = TRUE,
  assembly = organism
)

Arguments

`organism`	scientific name of organism, Homo sapiens, Danio rerio, Mus musculus, etc. See `biomartr:::get.ensembl.info()` for full list of supported organisms.
`output.dir`	directory to save downloaded data
`db`	database to use for genome and GTF, default adviced: "ensembl" (remember to set assembly_type to "primary_assembly", else it will contain haplotypes, very large file!). Alternatives: "refseq" (reference assemblies) and "genbank" (all assemblies)
`GTF`	logical, default: TRUE, download gtf of organism specified in "organism" argument. If FALSE, check if the downloaded file already exist. If you want to use a custom gtf from you hard drive, set GTF = FALSE, and assign: annotation <- getGenomeAndAnnotation(gtf = FALSE) annotation["gtf"] = "path/to/gtf.gtf". If db is not "ensembl", you will instead get a gff file.
`genome`	logical, default: TRUE, download genome of organism specified in "organism" argument. If FALSE, check if the downloaded file already exist. If you want to use a custom gtf from you hard drive, set `GTF = FALSE`, and assign: `annotation <- getGenomeAndAnnotation(genome = FALSE)` `annotation["genome"] = "path/to/genome.fasta"`. Will download the primary assembly from Ensembl.
`merge_contaminants`	logical, default TRUE. Will merge the contaminants specified into one fasta file, this considerably saves space and is much quicker to align with STAR than each contaminant on it's own. If no contaminants are specified, this is ignored.
`phix`	logical, default FALSE, download phiX sequence to filter out Illumina control reads. ORFik defines Phix as a contaminant genome. Phix is used in Illumina sequencers for sequencing quality control. Genome is: refseq, Escherichia phage phiX174. If sequencing facility created fastq files with the command `bcl2fastq`, then there should be very few phix reads left in the fastq files recieved.
`ncRNA`	logical or character, default FALSE (not used, no download), if TRUE or defned path, ncRNA is used as a contaminant reference. If TRUE, will try to find ncRNA sequences from the gtf file, usually represented as lncRNA (long noncoding RNA's). Will let you know if no ncRNA sequences were found in gtf. If not found try character input: Alternatives; "auto": Will try to find ncRNA file on NONCODE from organism, Homo sapiens -> human etc. "auto" will not work for all, then you must specify the name used by NONCODE, go to the link below and find it. If not "auto" / "" it must be a character vector of species common name (not scientific name) Homo sapiens is human, Rattus norwegicus is rat etc, download ncRNA sequence to filter out with. From NONCODE online server, if you cant find common name see: http://www.noncode.org/download.php/
`tRNA`	logical or character, default FALSE (not used, no download), tRNA is used as a contaminant genome. If TRUE, will try to find tRNA sequences from the gtf file, usually represented as Mt_tRNA (mature tRNA's). Will let you know if no tRNA sequences were found in gtf. If not found try character input: if not "" it must be a character vector to valid path of mature tRNAs fasta file to remove as contaminants on your disc. Find and download your wanted mtRNA at: http://gtrnadb.ucsc.edu/, or run trna-scan on you genome.
`rRNA`	logical or character, default FALSE (not used, no download), rRNA is used as a contaminant reference If TRUE, will try to find rRNA sequences from the gtf file, usually represented as rRNA (ribosomal RNA's). Will let you know if no rRNA sequences were found in gtf. If not found you can try character input: If "silva" will download silva SSU & LSU sequences for all species (250MB file) and use that. If you want a smaller file go to https://www.arb-silva.de/ If not "" or "silva" it must be a character vector to valid path of mature rRNA fasta file to remove as contaminants on your disc.
`gunzip`	logical, default TRUE, uncompress downloaded files that are zipped when downloaded, should be TRUE!
`remake`	logical, default: FALSE, if TRUE remake everything specified
`assembly_type`	character, default c("primary_assembly", "toplevel"). Used for ensembl only, specifies the genome assembly type. Searches for both primary and toplevel, and if both are found, uses the first by order (so primary is prioritized by default). The Primary assembly should usually be used if it exists. The "primary assembly" contains all the top-level sequence regions, excluding alternative haplotypes and patches. If the primary assembly file is not present for a species (only defined for standard model organisms), that indicates that there were no haplotype/patch regions, and in such cases, the 'toplevel file is used. For more details see: ensembl tutorial
`optimize`	logical, default FALSE. Create a folder within the folder of the gtf, that includes optimized objects to speed up loading of annotation regions from up to 15 seconds on human genome down to 0.1 second. ORFik will then load these optimized objects instead. Currently optimizes filterTranscript() function and loadRegion() function for 5' UTRs, 3' UTRs, CDS, mRNA (all transcript with CDS) and tx (all transcripts).
`gene_symbols`	logical default FALSE. If TRUE, will download and store all gene symbols for all transcripts (coding and noncoding)- In a file called: "gene_symbol_tx_table.fst" in same folder as txdb. hgcn for human, mouse symbols for mouse and rat, more to be added.
`uniprot_id`	logical default FALSE. If TRUE, will download and store all uniprot id for all transcripts (coding and noncoding)- In a file called: "gene_symbol_tx_table.fst" in same folder as txdb.
`pseudo_5UTRS_if_needed`	integer, default NULL. If defined > 0, will add pseudo 5' UTRs if 30 a leader.
`remove_annotation_outliers`	logical, default TRUE. Only for refseq. shall outlier lines be removed from the input annotation_file? If yes, then the initial annotation_file will be overwritten and the removed outlier lines will be stored at tempdir for further exploration. Among others Aridopsis refseq contains malformed lines, where this is needed
`notify_load_existing`	logical, default TRUE. If annotation exists (defined as: locally (a file called outputs.rds) exists in outputdir), print a small message notifying the user it is not redownloading. Set to FALSE, if this is not wanted
`assembly`	character, default is assembly = organism, which means getting the first assembly in list, otherwise the name of the assembly wanted, like "GCA_000005845" will get ecoli substrain k12, which is the most used ones for references. Usually ignore this for non bacterial species.

Details

Some files that are made after download:
- A fasta index for the genome
- A TxDb to speed up GTF/GFF reading
- Seperat of merged contaminant files
Files that can be made:
- Gene symbols (hgnc, etc)
- Uniprot ids (For name of protein structures)
If you want custom genome or gtf from you hard drive, assign existing paths like this:
annotation <- getGenomeAndAnnotation(GTF = "path/to/gtf.gtf", genome = "path/to/genome.fasta")

Value

a named character vector of path to genomes and gtf downloaded, and additional contaminants if used. If merge_contaminants is TRUE, will not give individual fasta files to contaminants, but only the merged one.

Examples


## Get Saccharomyces cerevisiae genome and gtf (create txdb for R)
#getGenomeAndAnnotation("Saccharomyces cerevisiae", tempdir(), assembly_type = "toplevel")
## Download and add pseudo 5' UTRs
#getGenomeAndAnnotation("Saccharomyces cerevisiae", tempdir(), assembly_type = "toplevel",
#  pseudo_5UTRS_if_needed = 100)
## Get Danio rerio genome and gtf (create txdb for R)
#getGenomeAndAnnotation("Danio rerio", tempdir())

output.dir <- "/Bio_data/references/zebrafish"
## Get Danio rerio and Phix contamints to deplete during alignment
#getGenomeAndAnnotation("Danio rerio", output.dir, phix = TRUE)

## Optimize for ORFik (speed up for large annotations like human or zebrafish)
#getGenomeAndAnnotation("Danio rerio", tempdir(), optimize = TRUE)

# Drosophila melanogaster (toplevel exists only)
#getGenomeAndAnnotation("drosophila melanogaster", output.dir = file.path(config["ref"],
# "Drosophila_melanogaster_BDGP6"), assembly_type = "toplevel")
## How to save malformed refseq gffs:
## First run function and let it crash:
#annotation <- getGenomeAndAnnotation(organism = "Arabidopsis thaliana",
#  output.dir = "~/Desktop/test_plant/",
#  assembly_type = "primary_assembly", db = "refseq")
## Then apply a fix (example for linux, too long rows):
# fixed_gff <- fix_malformed_gff("~/Desktop/test_plant/Arabidopsis_thaliana_genomic_refseq.gff")
## Then updated arguments:
# annotation <- c(fixed_gff, "~/Desktop/test_plant/Arabidopsis_thaliana_genomic_refseq.fna")
# names(annotation) <- c("gtf", "genome")
# Then make the txdb (for faster R use)
# makeTxdbFromGenome(annotation["gtf"], annotation["genome"], organism = "Arabidopsis thaliana")

Roleren/ORFik documentation built on April 25, 2024, 8:41 p.m.